QuoData GmbH services

Over and above such standard services as taking over tasks associated with sample preparation or analysis and evaluation, we offer specialized services such as consulting to develop tailor-made interlaboratory studies. Taking the proficiency test as an example, the following diagram is meant to illustrate what a typical interlaboratory test looks like, and to provide a succinct overview of the kind of services we offer.

In addition to our software for the planning and evaluation of interlaboratory studies, you can utilize our expertise as a service. Our all-inclusive service covers everything from logistics and organization of to execution and evaluation.

Our work focuses on the evaluation and planning of interlaboratory studies (ILS). Here`s a brief overview of the terminology surrounding interlaboratory studies:

The development of applied mathematical and statistical methods is a core competency of QuoData. We develop methods in order to assess quality and risk, to identify trends and to establish mathematical models for the relation between different variables. QuoData places special emphasis on experimental design and, if experiments are not feasible, on sampling design. Appropriate experimental or sampling designs may improve the confidence of the outcome of the statistical analysis substantially.

In R&D projects we provide a strategy of experimental studies and evaluate the data statistically. We use highly efficient designs and use up-to-date statistical methods of optimization. You get meaningful reports (almost) just in time. We present the results within a workshop or a teleconference, and we also can train your staff in using new optimation techniques.

QuoData realizes the validation of your measurement method according to the requirements of ISO 17025. We realize validation studies also for methods where standardized validation approaches cannot be applied. This holds not only for quantitative but also for semi-quantitative or qualitative test methods. Validation allows to characterize different measurement methods with regard to the measurement deviation (error), with regard to the measurement uncertainty, and with regard to sources of measurement deviation.